dada22231 commited on
Commit
cec0103
1 Parent(s): a5165f9

End of training

Browse files
Files changed (2) hide show
  1. README.md +171 -0
  2. adapter_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,171 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ license: llama3
4
+ base_model: Orenguteng/Llama-3-8B-Lexi-Uncensored
5
+ tags:
6
+ - axolotl
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: 5589168d-ec89-491d-b56d-03288e102c16
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
17
+ <details><summary>See axolotl config</summary>
18
+
19
+ axolotl version: `0.4.1`
20
+ ```yaml
21
+ adapter: lora
22
+ base_model: Orenguteng/Llama-3-8B-Lexi-Uncensored
23
+ bf16: auto
24
+ chat_template: llama3
25
+ cosine_min_lr_ratio: 0.1
26
+ data_processes: 16
27
+ dataset_prepared_path: null
28
+ datasets:
29
+ - data_files:
30
+ - 71c67ff05390e157_train_data.json
31
+ ds_type: json
32
+ format: custom
33
+ path: /workspace/input_data/71c67ff05390e157_train_data.json
34
+ type:
35
+ field_input: context
36
+ field_instruction: question
37
+ field_output: answer
38
+ format: '{instruction} {input}'
39
+ no_input_format: '{instruction}'
40
+ system_format: '{system}'
41
+ system_prompt: ''
42
+ debug: null
43
+ deepspeed: null
44
+ device_map: auto
45
+ do_eval: true
46
+ early_stopping_patience: 1
47
+ eval_batch_size: 1
48
+ eval_sample_packing: false
49
+ eval_steps: 25
50
+ evaluation_strategy: steps
51
+ flash_attention: true
52
+ fp16: null
53
+ fsdp: null
54
+ fsdp_config: null
55
+ gradient_accumulation_steps: 32
56
+ gradient_checkpointing: true
57
+ group_by_length: true
58
+ hub_model_id: dada22231/5589168d-ec89-491d-b56d-03288e102c16
59
+ hub_strategy: checkpoint
60
+ hub_token: null
61
+ learning_rate: 0.0001
62
+ load_in_4bit: false
63
+ load_in_8bit: false
64
+ local_rank: null
65
+ logging_steps: 1
66
+ lora_alpha: 64
67
+ lora_dropout: 0.05
68
+ lora_fan_in_fan_out: null
69
+ lora_model_dir: null
70
+ lora_r: 32
71
+ lora_target_linear: true
72
+ lora_target_modules:
73
+ - q_proj
74
+ - v_proj
75
+ lr_scheduler: cosine
76
+ max_grad_norm: 1.0
77
+ max_memory:
78
+ 0: 70GiB
79
+ 1: 70GiB
80
+ 2: 70GiB
81
+ 3: 70GiB
82
+ max_steps: 25
83
+ micro_batch_size: 1
84
+ mlflow_experiment_name: /tmp/71c67ff05390e157_train_data.json
85
+ model_type: AutoModelForCausalLM
86
+ num_epochs: 3
87
+ optim_args:
88
+ adam_beta1: 0.9
89
+ adam_beta2: 0.95
90
+ adam_epsilon: 1e-5
91
+ optimizer: adamw_torch
92
+ output_dir: miner_id_24
93
+ pad_to_sequence_len: true
94
+ resume_from_checkpoint: null
95
+ s2_attention: null
96
+ sample_packing: false
97
+ save_steps: 25
98
+ save_strategy: steps
99
+ sequence_len: 2048
100
+ strict: false
101
+ tf32: false
102
+ tokenizer_type: AutoTokenizer
103
+ torch_compile: false
104
+ train_on_inputs: false
105
+ trust_remote_code: true
106
+ val_set_size: 50
107
+ wandb_entity: null
108
+ wandb_mode: online
109
+ wandb_name: 5589168d-ec89-491d-b56d-03288e102c16
110
+ wandb_project: Public_TuningSN
111
+ wandb_runid: 5589168d-ec89-491d-b56d-03288e102c16
112
+ warmup_ratio: 0.04
113
+ weight_decay: 0.01
114
+ xformers_attention: null
115
+
116
+ ```
117
+
118
+ </details><br>
119
+
120
+ # 5589168d-ec89-491d-b56d-03288e102c16
121
+
122
+ This model is a fine-tuned version of [Orenguteng/Llama-3-8B-Lexi-Uncensored](https://huggingface.co/Orenguteng/Llama-3-8B-Lexi-Uncensored) on the None dataset.
123
+ It achieves the following results on the evaluation set:
124
+ - Loss: 0.3838
125
+
126
+ ## Model description
127
+
128
+ More information needed
129
+
130
+ ## Intended uses & limitations
131
+
132
+ More information needed
133
+
134
+ ## Training and evaluation data
135
+
136
+ More information needed
137
+
138
+ ## Training procedure
139
+
140
+ ### Training hyperparameters
141
+
142
+ The following hyperparameters were used during training:
143
+ - learning_rate: 0.0001
144
+ - train_batch_size: 1
145
+ - eval_batch_size: 1
146
+ - seed: 42
147
+ - distributed_type: multi-GPU
148
+ - num_devices: 4
149
+ - gradient_accumulation_steps: 32
150
+ - total_train_batch_size: 128
151
+ - total_eval_batch_size: 4
152
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
153
+ - lr_scheduler_type: cosine
154
+ - lr_scheduler_warmup_steps: 2
155
+ - training_steps: 25
156
+
157
+ ### Training results
158
+
159
+ | Training Loss | Epoch | Step | Validation Loss |
160
+ |:-------------:|:------:|:----:|:---------------:|
161
+ | 1.1964 | 0.0192 | 1 | 2.8640 |
162
+ | 0.486 | 0.4811 | 25 | 0.3838 |
163
+
164
+
165
+ ### Framework versions
166
+
167
+ - PEFT 0.13.2
168
+ - Transformers 4.46.0
169
+ - Pytorch 2.5.0+cu124
170
+ - Datasets 3.0.1
171
+ - Tokenizers 0.20.1
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:614d5d92f5062b2a3b5aa2a2c0fdafbe935c6d23626f27358662f9644446fb81
3
+ size 335706186